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Settling the score: variant prioritization and Mendelian disease
Karen Eilbeck1, Aaron Quinlan1,2, Mark Yandell2
1Department of Biomedical Informatics, School of Medicine, University of Utah, 421 Wakara Way, Suite 120, Salt Lake City, Utah 84108, USA.
Nature Reviews. Genetics
|August 15, 2017
Summary
Identifying disease-causing genetic variants from sequencing data is challenging. This review examines computational tools for variant prioritization, discussing their utility and limitations in diagnosing Mendelian diseases.
Area of Science:
- Genetics
- Bioinformatics
- Genomic Medicine
Background:
- Investigating Mendelian diseases with exome or genome sequencing generates numerous candidate genetic variants.
- Distinguishing pathogenic variants requires sophisticated analysis and interpretation strategies.
- Existing computational tools and clinical guidelines aid in variant prioritization but have limitations.
Purpose of the Study:
- To review the strengths and weaknesses of computational approaches for genetic variant prioritization.
- To explain the role of these tools in both clinical diagnostics and genetic discovery.
- To discuss the impact of whole-genome sequencing on variant interpretation.
Main Methods:
- Review of widely used computational variant prioritization tools.
- Analysis of existing clinical guidelines for variant interpretation.
- Discussion of genotype-phenotype association and gene prioritization methods.
Main Results:
- Computational tools offer valuable support but can also misinform expert reviewers.
- Variant prioritization is interconnected with gene prioritization and burden testing.
- Whole-genome sequencing presents new opportunities and challenges for variant interpretation.
Conclusions:
- Effective variant prioritization is crucial for accurate Mendelian disease diagnosis.
- Understanding the limitations of computational tools is essential for expert reviewers.
- Further development is needed to optimize variant interpretation in the era of whole-genome sequencing.
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